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Construction, categorization, and consensus: student generated computational artifacts as a context for disciplinary reflection

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Abstract

There are increasing calls to prepare K-12 students to use computational tools and principles when exploring scientific or mathematical phenomena. The purpose of this paper is to explore whether and how constructionist computer-supported collaborative environments can explicitly engage students in this practice. The Categorizer is a Javascript-based interactive gallery that allows members of a learning community to contribute computational artifacts they have constructed to a shared collection. Learners can then analyze the collection of artifacts, and sort them into user-defined categories. In a formative case study of the Categorizer for a fractal activity in three middle grade (ages 11–14) classrooms, there was evidence that participating students began to evaluate fractals based on structural and mathematical properties, and afterward could create algorithms that would generate fractals with particular area reduction rates. Further analysis revealed that students’ construction and categorization experiences could be better integrated by explicitly scaffolding discussion and negotiation of the categorization schemes they develop. This led to the development of a new module that enables teachers and students to explore points of agreement and disagreement across student categorization schemes. I conclude with a description of limitations of the study and environment, implications for the broader community, and future work.

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Notes

  1. Items 1 and 2 on the post questionnaire were designed to be more difficult than those on the pre questionnaire. Pre–post differences on both items were not significant (Item 1, W = 12, p = n.s.; Item 2, W = 28, p = n.s.).

  2. Pseudonym.

References

  • Alligood, K. T., Sauer, T. D., & Yorke, J. A. (2000). Chaos: An introduction to dynamical systems. New York: Springer.

    Google Scholar 

  • Ares, N., Stroup, W. M., & Schademan, A. R. (2009). The power of mediating artifacts in group-level development of mathematical discourses. Cognition and Instruction, 27(1), 1–24.

    Article  Google Scholar 

  • Bailey, D. H., & Borwein, J. M. (2011). Exploratory experimentation and computation. Notices of the AMS, 58(10), 1410–1419.

    Google Scholar 

  • Baish, J. W., & Jain, R. K. (2000). Fractals and cancer. Cancer Research, 60(14), 3683–3688.

    Google Scholar 

  • Barr, D., Harrison, J., & Conery, L. (2011). Computational thinking: A digital age skill for everyone. Learning & Leading with Technology, 38(6), 20–23.

    Google Scholar 

  • Bers, M. U. (2010). The TangibleK robotics program: Applied computational thinking for young children. Early Childhood Research & Practice, 12(2). http://ecrp.uiuc.edu/v12n2/bers.html.

  • Blikstein, P., & Wilensky, U. (2009). An atom is known by the company it keeps: A constructionist learning environment for materials science using agent-based modeling. International Journal of Computers for Mathematical Learning, 14(2), 81–119.

    Article  Google Scholar 

  • Brady, C., White, T., Davis, S., & Hegedus, S. (2013). SimCalc and the networked classroom. In S. J. Hegedus & J. Roschelle (Eds.), The SimCalc vision and contributions: Democratizing access to important mathematics (pp. 99–121). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges in creating complex interventions in classroom settings. Journal of the Learning Sciences, 2(22), 141–178.

    Article  Google Scholar 

  • Chandrasekharan, S. (2009). Building to discover: A common coding model. Cognitive Science, 33(6), 1059–1086.

    Article  Google Scholar 

  • Chi, M. T., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5(2), 121–152.

    Article  Google Scholar 

  • Clark, A. C., & Ernst, J. V. (2008). STEM-based computational modeling for technology education. The Journal of Technology Studies, 34(1), 20–27.

    Google Scholar 

  • Cobb, P., Confrey, J., diSessa, A., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(9), 9–13.

    Article  Google Scholar 

  • Collins, A. (1992). Toward a design science of education. In E. Scanlon & T. O’Shea (Eds.), New directions in educational technology. Berlin: Springer.

    Google Scholar 

  • Common Core State Standards Initiative. (2010). Common core state standards for mathematics. Retrieved December 15, 2012, from http://www.corestandards.org/Math.

  • de Jong, T., Weinberger, A., Girault, I., Kluge, A., Lazonder, A. W., Pedaste, M., et al. (2012). Using scenarios to design complex technology-enhanced learning environments. Educational Technology Research and Development, 60(5), 883–901.

    Article  Google Scholar 

  • Demko, S., Hodges, L., & Naylor, B. (1985). Construction of fractal objects with iterated function systems. AC SIGGRAPH Computer Graphics, 19(3), 271–278.

    Article  Google Scholar 

  • Dierbach, C., Hochheiser, H., Collins, S., Jerome, G., Ariza, C., Kelleher, T., & Kaza, S. (2011). A model for piloting pathways for computational thinking in a general education curriculum. In Proceedings of the 42nd ACM Technical Symposium on Computer Science Education (pp. 257–262). ACM.

  • diSessa, A. (2000). Changing minds: Computers, learning, and literacy. Cambridge, MA: MIT Press.

    Google Scholar 

  • diSessa, A. A., & Abelson, H. (1986). Boxer: A reconstructible computational medium. Communications of the ACM, 29(9), 859–868.

    Article  Google Scholar 

  • Edelson, D. C., Pea, R. D., & Gomez, L. M. (1996). The collaboratory notebook. Communications of the ACM, 39, 32–33.

    Article  Google Scholar 

  • Forte, A., & Bruckman, A. (2007). Constructing text: Wiki as a toolkit for (collaborative?) learning. In International Symposium on Wikis: Proceedings of the 2007 International Symposium on Wikis (Vol. 21, No. 25, pp. 31–42).

  • Glaser, B. G., & Strauss, A. L. (1967). Discovery of grounded theory: Strategies for qualitative research. Mill Valley, CA: Sociology Press.

    Google Scholar 

  • Goldstone, R. L., & Wilensky, U. (2008). Promoting transfer by grounding complex systems principles. The Journal of the Learning Sciences, 17(4), 465–516.

    Article  Google Scholar 

  • Grover, S., & Pea, R. (2013). Computational thinking in K-12: A review of the state of the field. Educational Researcher, 42(1), 38–43.

    Article  Google Scholar 

  • Hambrusch, S., Hoffmann, C., Korb, J. T., Haugan, M., & Hosking, A. L. (2009). A multidisciplinary approach towards computational thinking for science majors. In ACM SIGCSE Bulletin (Vol. 41, No. 1, pp. 183–187). New York: ACM.

  • Harel, I., & Papert, S. (1991). Constructionism. New York: Ablex Publishing.

    Google Scholar 

  • Hegedus, S. J., & Moreno-Armella, L. (2009). Intersecting representation and communication infrastructures. ZDM, 41(4), 399–412.

    Article  Google Scholar 

  • Hmelo-Silver, C. E., Jordan, R., Liu, L., & Chernobilsky, E. (2011). Representational tools for understanding complex computer-supported collaborative learning environments. Analyzing Interactions in CSCL, 12, 83–106.

    Article  Google Scholar 

  • Jackson, S., Krajcik, J., & Soloway, E. (2000). Model-It: A design retrospective. In M. J. Jacobson & R. B. Kozma (Eds.), Advanced designs for the technologies of learning: Innovations in science and mathematics education (pp. 77–116). New York: Wiley.

    Google Scholar 

  • Kafai, Y., & Resnick, M. (1996). Constructionism in practice: Designing, thinking, and learning in a digital world. Mahwah, NJ: Lawrence Erlbaum Associates.

    Google Scholar 

  • Kahn, K. (1996). ToonTalk™: An animated programming environment for children. Journal of Visual Languages & Computing, 7(2), 197–217.

    Article  Google Scholar 

  • Khan, S. (2008). The case in case-based design of educational software: A methodological interrogation. Educational Technology Research and Development, 56, 423–447.

    Article  Google Scholar 

  • Konold, C., & Miller, C. D. (2005). TinkerPlots: Dynamic data exploration [Computer software]. Emeryville, CA: Key Curriculum Press.

    Google Scholar 

  • Kress, G., & Van Leeuwen, T. V. (2001). Multimodal discourse: The modes and media of contemporary communication. London: Hodder Arnold.

    Google Scholar 

  • Kurland, D. M., Pea, R. D., Clement, C., & Mawby, R. (1986). A study of the development of programming ability and thinking skills in high school students. Journal of Educational Computing Research, 2, 429–458.

    Article  Google Scholar 

  • Leinhardt, G., Zaslavsky, O., & Stein, M. K. (1990). Functions, graphs, and graphing: Tasks, learning, and teaching. Review of Educational Research, 60(1), 1–64.

    Article  Google Scholar 

  • Linn, M. C., Clark, D., & Slotta, J. D. (2003). WISE design for knowledge integration. Science Education, 87(4), 517–538.

    Article  Google Scholar 

  • National Council of Teachers of Mathematics. (2000). Principles and standards for school mathematics. Reston, VA: NCTM.

    Google Scholar 

  • National Council of Teachers of Mathematics (2003). Fractal tool [computer software]. NCTM Illuminations Resource Website, Retrieved August 17, 2013, from http://illuminations.nctm.org/ActivityDetail.aspx?ID=17.

  • National Research Council. (2012). A framework for K-12 science education: Practices, crosscutting concepts, and core ideas. Washington, DC: The National Academies Press.

    Google Scholar 

  • National Research Council Committee for the Workshops on Computational Thinking. (2010). Report of a workshop on the scope and nature of computational thinking. Washington, DC: National Academies Press.

    Google Scholar 

  • National Research Council Committee on Science Learning, & Kindergarten Through Eighth Grade. (2007). In R. A. Duschl, H. A. Schweingruber, & A. W. Shouse (Eds.), Taking science to school: Learning and teaching science in grades K-8. Washington, DC: National Academies Press.

    Google Scholar 

  • Noss, R., & Hoyles, C. (2006). Exploring mathematics through construction and collaboration. In: R. K Sawyer (Ed.), Cambridge handbook of the learning sciences (pp. 389–405). Cambridge: Cambridge University Press.

  • Papert, S. (1980). Mindstorms: Children, computers, and powerful ideas. New York: Basic Books Inc.

    Google Scholar 

  • Papert, S. (1996). An exploration in the space of mathematics educations. International Journal of Computers for Mathematical Learning, 1(1), 95–123.

    Google Scholar 

  • Renninger, K. A., & Shumar, W. (2002). Community building with and for teachers at the Math Forum. In K. A. Renninger & W. Shumar (Eds.), Building virtual communities: Learning and change in cyberspace (pp. 60–95). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • Repenning, A., Ioannidou, A., & Zola, J. (2000). AgentSheets: End-user programmable simulations. Journal of Artificial Societies and Social Simulation, 3(3), 351.

    Google Scholar 

  • Repenning, A., Webb, D., & Ioannidou, A. (2010, March). Scalable game design and the development of a checklist for getting computational thinking into public schools. In Proceedings of the 41st ACM Technical Symposium on Computer Science Education (pp. 265–269). New York: ACM.

  • Resnick, M., Maloney, J., Monroy-Hernández, A., Rusk, N., Eastmond, E., Brennan, K., et al. (2009). Scratch: Programming for all. Communications of the ACM, 52(11), 60–67.

    Article  Google Scholar 

  • Romberg, T. A., & Kaput, J. J. (1999). Mathematics worth teaching, mathematics worth understanding. In E. Fennema & T. A. Romberg (Eds.) Mathematics classrooms that promote understanding (pp. 3–17). Mahwah, NJ: Lawrence Erlbaum Associates.

  • Sabelli, N. H. (2006). Complexity, technology, science, and education. Journal of the Learning Sciences, 15(1), 5.

    Article  Google Scholar 

  • Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. The Journal of the Learning Sciences, 3(3), 265–283.

    Article  Google Scholar 

  • Sherin, B. L. (2001). A comparison of programming languages and algebraic notation as expressive languages for physics. International Journal of Computers for Mathematical Learning, 6(1), 1–61.

    Article  Google Scholar 

  • Slotta, J. D., & Aleahmad, T. (2009). WISE technology lessons: Moving from a local proprietary system to a global open source framework. Research and Practice in Technology Enhanced Learning, 4(2), 169–189.

    Article  Google Scholar 

  • Techsmith Corporation (2004). Camtasia [Computer software].

  • Tissenbaum, M., Lui, M., & Slotta, J. D. (2012). Co-designing collaborative smart classroom curriculum for secondary school science. Journal of Universal Computer Science, 18(3), 327–352.

    Google Scholar 

  • Wang, F., & Hannafin, M. J. (2005). Design-based research and technology-enhanced learning environments. Educational Technology Research and Development, 53(4), 5–23.

    Article  Google Scholar 

  • White, T. (2009). Encrypted objects and decryption processes: Problem-solving with functions in a learning environment based on cryptography. Educational Studies in Mathematics, 72(1), 17–37.

    Article  Google Scholar 

  • Wilensky, U. (1999). NetLogo [Computer Software]. Evanston, IL: Center for Connected Learning, Northwestern University.

    Google Scholar 

  • Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: Learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171–209.

    Article  Google Scholar 

  • Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems approach to making sense of the world. Journal of Science Education and Technology, 8(1), 3–19.

    Article  Google Scholar 

  • Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.

    Article  Google Scholar 

  • Yin, R. K. (2008). Case study research: Design and methods. Thousand Oaks, CS: AGE Publications.

    Google Scholar 

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Acknowledgments

Many thanks to the teachers, students, and school administrators who worked with me on this project. It would not have been possible without the help of Aditi Wagh, Nathan Holbert, Forrest Stonedahl, Susa Stonedahl, Christopher Macrander, and Uri Wilensky. I am also grateful for feedback on earlier versions of this manuscript provided by several anonymous reviewers, J. Michael Spector, Jenna Conversano, and Ben Shapiro.

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  1. Tufts University, Medford, MA, USA

    Michelle Hoda Wilkerson-Jerde

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  1. Michelle Hoda Wilkerson-Jerde
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Correspondence to Michelle Hoda Wilkerson-Jerde.

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Wilkerson-Jerde, M.H. Construction, categorization, and consensus: student generated computational artifacts as a context for disciplinary reflection. Education Tech Research Dev 62, 99–121 (2014). https://doi.org/10.1007/s11423-013-9327-0

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